Author, as appears in the article.: Alvarado-Pérez JC; Garcia MA; Puig D
Department: Enginyeria Informàtica i Matemàtiques
URV's Author/s: Puig Valls, Domènec Savi
Keywords: Cluster inductions Dimensionality reductions Ensemble learning Manifold approximations Online processing Topological preservations Unsupervised deep networks
Abstract: Dimension reduction aims to project a high-dimensional dataset into a low-dimensional space. It tries to preserve the topological relationships among the original data points and/or induce clusters. NetDRm, an online dimensionality reduction method based on neural ensemble learning that integrates different dimension reduction methods in a synergistic way, is introduced. NetDRm is designed for datasets of multidimensional points that can be either structured (e.g., images) or unstructured (e.g., point clouds, tabular data). It starts by training a collection of deep residual encoders that learn the embeddings induced by multiple dimension reduction methods applied to the input dataset. Subsequently, a dense neural network integrates the generated encoders by emphasizing topological preservation or cluster induction. Experiments conducted on widely used multidimensional datasets (point-cloud manifolds, image datasets, tabular record datasets) show that the proposed method yields better results in terms of topological preservation ((Formula presented.) curves), cluster induction (V measure), and classification accuracy than the most relevant dimension reduction methods.
Thematic Areas: Artificial intelligence Automation & control systems Computer science, artificial intelligence Computer vision and pattern recognition Control and systems engineering Electrical and electronic engineering Human-computer interaction Materials science (miscellaneous) Mechanical engineering Robotics
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: domenec.puig@urv.cat
Author identifier: 0000-0002-0562-4205
Record's date: 2024-10-12
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://onlinelibrary.wiley.com/doi/10.1002/aisy.202400178
Papper original source: Advanced Intelligent Systems.
APA: Alvarado-Pérez JC; Garcia MA; Puig D (2024). Dimension Reduction of Multidimensional Structured and Unstructured Datasets through Ensemble Learning of Neural Embeddings. Advanced Intelligent Systems, (), -. DOI: 10.1002/aisy.202400178
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Article's DOI: 10.1002/aisy.202400178
Entity: Universitat Rovira i Virgili
Journal publication year: 2024
Publication Type: Journal Publications